Presentation

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The amount of information existing in the world is following an exponential growth, and this trend is maintained unstoppable. These data come from the most varied fields: climatological observations, research on the cosmos from satellites and observatories, social networks, commercial transactions, consultations and navigation observable on the Internet, information contained in clinical databases of patients, and so on. Data is the basic raw material in the same areas in which it is generated or in others. For example, information from social networks and Internet surfing is useful in criminological research or in the fight against terrorism or in the creation of customer profiles for companies. It is therefore necessary to search for and collect data, select them, process them, visualize them, interpret them, turn them into useful information and knowledge, and use them in decision-making. This is, in very general terms, the area in which this doctoral programme is situated.

The technologies needed to carry out these tasks are traditionally known as Data Analysis, which has evolved to deal with Big Data, in reference to the enormous volume of information, and also assume that the information is constantly changing, is organized in different formats or is even unorganized, and its collection and processing is required at high speed. This is currently synthesized in the paradigm called the "3 V's": volume, variety and speed. Although data analysis is not new, the quantity, quality, format and sources of information have been transformed in such a way that conventional data collection and processing techniques do not work in this context. New techniques, methodology and tools need to be developed, and it is currently a major research challenge. To develop them, solid knowledge is required in statistics, computing, analysis and mathematics, giving rise to a new profile of researcher and professional called "data scientist". In data science it is also necessary to know the working domains (finance, marketing, medicine, meteorology, sociology, etc.), and to have organizational skills in information and communication, with the aim of disseminating what has been found in the field in which you are researching.

The doctoral programme "Data Science" of the Faculty of Statistical Studies has a broad interdisciplinary character whose common denominator is research in some of the phases involved in the efficient treatment of information, understood in a broad sense (texts, images, spatial-temporal data, etc.). Its objective is to train researchers whose specialisation focuses on one of the research lines of the doctoral programme, all of which are related to Data Science techniques. In this way, it will be possible to carry out research in the collection and structuring of information, in the processing of data with greater computational efficiency, in the analysis of the databases generated as well as in the research environments from which this information is extracted, among other fields.

The doctoral programme "Data Science" is part of the R&D&I strategy of the Complutense University of Madrid and involves the collaboration of different public and private bodies from around the world.

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